1. Technical Field
The present disclosure is related to a system and method for the analysis of electrocardiogram (ECG) signals and more particularly to the detection and location of the R peaks of an input ECG signal.
2. Technical Background
Monitoring of biopotential electrical signals is currently used in many applications. For example, ambulatory monitoring of an electrocardiogram (ECG) taken from a biological subject (patient) can be used to evaluate the heart condition of a patient, like ischemia, late potentials, heart rate variability etc. This is normally performed by measuring the patient's cardiac rhythm over an extended period of time to determine the regularity of the heart beat received. The biopotential electrical signals are measured during normal activity of the monitoring biological subjects, including any physical and psychological changes. This approach allows the evaluation of dynamically changing cardiac electrical phenomena that are often transient and of brief duration. Any abnormalities detected at this stage may indicate the existence of a heart condition, such as arrhythmia, which can be fatal and requires continuous monitoring to ensure the occurrence of the faster, slower or irregular heart rhythms. In this case, accuracy in detecting such abnormalities is of paramount importance since a wrong reading of the data received can compromise the life of the patient. Currently, there is a need for the development of battery powered portable systems that are small enough to be worn or carried comfortably by the patient without affecting his day to day activities.
The basic requirements of such portable, battery-powered systems are low power consumption and high accuracy in the detection of anomalies. The design will need to meet different specification compared to that of the hospitalized monitoring systems. This is due to the embedded algorithms required in such portable systems. The algorithm must satisfy the memory and computational complexity constraints of low powered embedded systems. Besides these constraints, an additional challenge for the embedded algorithms in portable systems is the extraction of information from noisy signals. The noise and motion artifacts of the biopotential signals measured by a portable system is of a higher order compared to those added to the biopotential signal measured in a controlled environment, for example in hospitalized monitoring. At the same time the need for accuracy and reliability remains high since it concerns the human health.
Known techniques presented in the state-of-the-art require at least high computational complexity and as a result most of them are not applicable in a low power embedded application.
A know solution that is applicable for ambulatory and low-power applications is described in patent application EP 2 298 164 A2, and mainly used for the calculation of the average heart bit rate (HBR). A problem with this solution though is that it is not accurate and reliable enough to be applied for the calculation of the heart bit rate variability (HBRV).